The present invention concerns with a high-efficiency compression coding of digital image information or data.
The information coding intended for improving or enhancing the efficiency of transmission by reducing the redundancy of the information such as video or the like information is known as a high-efficiency compression coding. One of the methods of realizing the compression coding resides in a block encoding in which a predetermined number of samples of image information is collected or grouped in a unit referred to as the block, wherein the compression of the samples is performed within each block. As typical ones of the block encoding, there can be mentioned an orthogonal transformation technique in which the samples within each block undergo the orthogonal transformation to be subsequently quantized and a vector quantization technique in which the samples are straightforwardly quantized on the block-by-block basis. In both of the coding techniques mentioned above, samples are compressed by taking advantage of strong or intensive correlation existing between the adjacent image samples. It is thus preferred that the samples within the block are located mutually as close as possible.
By way of example, a block encoding method according to which each block is composed of eight samples will be considered below. FIG. 13(a) of the accompanying drawings illustrates a one-dimensional block encoding method. It will be seen that the samples located at opposite ends are distance significantly from each other. In constant, in the case of a two-dimensional block encoding method illustrated in FIG. 13(b), the distance between the samples located at the opposite ends is appreciably shortened. Additionally, for the image information exhibiting continuity also in the direction along the time axis such as television (TV) signal, the distance between the samples located at the opposite ends can further be reduced by applying a three-dimensional block encoding technique illustrated in FIG. 13(b). To say in another way, the two-dimensional or three-dimensional block encoding of image information can realize the compression of the samples within a block at a very high ratio when compared with the one-dimensional block encoding.
Next, description will be made of the orthogonal transformation by taking as an example the Hadamard transformation which is a typical one of the orthogonal transformations and facilitates hardware implementation.
In the first place, samples are divided or grouped into blocks each including eight samples located adjacent to one another. According to the Hadamard transformation, a given block is represented by X=(x.sub.1, x.sub.2, . . . , x.sub.8) and subjected to the transformation mentioned below to obtain orthogonal sequency Y=(y.sub.1, y.sub.2, . . . , y.sub.8). Namely, EQU Y=H.multidot.X (1)
where H is represented by the following matrix referred to as the Hadamard matrix. ##EQU1##
Reversely, the original information X can be reconstituted or regenerated when the orthogonal sequency or component Y is subjected to an inverse transformation given by EQU X=H.sup.-1 .multidot.X=H.multidot.X (3)
In general, after the orthogonal transformation, remarkable differences in energy level make appearance among the individual orthogonal sequencies Y=(y.sub.1, y.sub.2, . . . , y.sub.8). Under the circumstance, a greater number of bits are allocated to the orthogonal sequency or component having a high energy level while a smaller number of bits are allocated to the orthogonal component of low energy level, to thereby make it possible to reduce the number of bits as a whole.
In the high-efficiency compression coding briefed above, the two-dimensional or three-dimensional block encoding is generally adopted. In the case of the two-dimensional block encoding, however, remarkable distortion may occur when the samples of image information within a block vary significantly in respect to magnitude, because then the correlation between the samples is correspondingly reduced or enfeebled.
In contrast, in the case of the three-dimensional block encoding, the correlation in the direction along the time axis can be held very high since the samples of image information vary little in that direction, which in turn means that a higher compression of the sampled data can be accomplished when compared with the two-dimensional block encoding. However, when the data samples exhibit significant diversity in magnitude in the time axis direction (i.e. in the direction coinciding with the time axis or base), correlation in that direction will be lost to a significant extent, giving rise to a problem that remarkable distortion takes place to a disadvantage.
Next, the difficulties accompanying the block encoding will be elucidated in conjunction with the one-dimensional eighth-order Hadamard transformation.
FIG. 14(a) of the accompanying drawings shows a sequence of sampled values of image information. As will be seen in the figure, the sampled value rises up steeply at a time point T. When the image information of this sort is subjected to the orthogonal transformation, concentration of energy occurs at a particular orthogonal sequency component, involving remarkable distortion. Upon the inverse transformation, the distortion will be dispersed among all the samples in an associated block, as a result of which the regenerated or decoded image information suffers remarkable distortion undesirably as illustrated in FIG. 14(b) where an extremely large peak value makes appearance, whereby the visual quality of the resulting image is remarkably degraded. As will now be appreciated, the orthogonal transformation applied to the image information in which steep or non-smooth variation occurs between the adjacent samples results in a great degradation in the quality of the reproduced image.